Detecting roadway targets within a multiple beam radar system

ABSTRACT

The present invention extends to methods, systems, and computer program products for detecting targets across beams at roadway intersections. Embodiments of the invention include tracking a target across a plurality of beams of a multiple beam radar system in a roadway intersection and updating track files for targets within a roadway intersection. Returns from a plurality of radar beams monitoring a roadway intersection are divided into range bins. Identified energy in the range bins is used to compute the position of targets within a roadway intersection. When the position of a target is computed, it is determined if the position is a new position for an existing target or if the position is the position of a new target.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. patent application Ser. No.14/164,102, entitled “Detecting Roadway Targets Across Beams”, filedJan. 24, 2014, which is a continuation of U.S. patent application Ser.No. 12/710,736, entitled “Detecting Roadway Targets Across BeamsIncluding Filtering Computed Positions”, filed Feb. 23, 2010, which isnow U.S. Pat. No. 8,665,113 issued Mar. 4, 2014, which is incorporatedby reference herein in its entirety, which claims the benefit of andpriority to U.S. Provisional Application No. 61/185,005, entitled“Detecting Targets in Roadway Intersections and Tracking Targets AcrossBeams”, filed on Jun. 8, 2009, which is incorporated by reference hereinin its entirety. U.S. patent application Ser. No. 12/710,736, entitled“Detecting Roadway Targets Across Beams Including Filtering ComputedPositions”, filed Feb. 23, 2010, which is now U.S. Pat. No. 8,665,113issued Mar. 4, 2014, is also a continuation-in-part of U.S. patentapplication Ser. No. 11/614,250, entitled “Detecting Targets in RoadwayIntersections”, filed Dec. 21, 2006, which is now U.S. Pat. No.7,889,097 issued Feb. 15, 2011, which is incorporated by referenceherein in its entirety, and also is a continuation-in-part of U.S.patent application Ser. No. 12/502,965, entitled “Detecting Targets InRoadway Intersections”, filed Jul. 14, 2009, which is acontinuation-in-part of U.S. patent application Ser. No. 11/264,339,entitled “Systems and Methods for Configuring Intersection DetectionZones”, filed Oct. 31, 2005, which is now U.S. Pat. No. 7,573,400,issued Aug. 11, 2009, both of which are incorporated by reference hereinin their entirety.

BACKGROUND Background and Relevant Art

The use of traffic sensors for the actuation of traffic signal lightslocated at roadway intersections is quite common. Generally, suchtraffic sensors can provide input used to properly actuate trafficcontrol devices in response to the detection or lack of detection ofvehicles. For example, traffic sensors can enable a traffic controldevice to skip unnecessary signal phases, such as, for example, skippinga left hand turn phase when no vehicles are detected in a correspondingleft hand turn lane.

Traffic sensors can also enable a traffic signal to increase green lightduration for major arterials by only signaling the green light in theminor cross streets when vehicles are detected on the minor crossstreets and thus minimizing the red light for a major arterial. Thus,traffic sensors assist in properly actuating a signalized intersectionto improve traffic flow. In addition to the actuation of signalizedintersections of roadways for automobile traffic, traffic sensors arealso used for the actuation of intersections of a roadway for automobiletraffic with a railway.

Unfortunately, the cost of traffic sensors, the cost of correspondinginstallation, and the subsequent maintenances costs can be relativelyhigh. Thus, traffic sensors and related costs can become a significantexpenditure for municipalities. The high installation costs arise atleast in part from the need to shut down lanes of traffic and cut intothe roadway surface. High maintenance costs arise from the need torepair and reconfigure sensors that do not consistently perform well.

Typically, traffic signal lights have been actuated using inductive loopdetectors embedded in the roadway. Inductive loop detectors are veryexpensive to install since lane closures are necessary. The high cost iscompounded, especially for multi-lane roadways, since at least oneinductive loop detector is required for each detection zone (e.g., lefthand turn lane detection zones, through lane detection zones, and righthand turn lane detection zones). Furthermore, inductive loop detectortechnology is often unreliable and inductive loop detectors require agreat deal of calibration.

Similar to inductive loop detectors, magnetometer detectors are embeddedin the roadway surface and require lane closures to install.Furthermore, some of these detectors are dependent on batteries foroperation, bringing into question the usable life of the sensor.Additionally, the sensors must be replaced or reinstalled when theroadway is resurfaced.

Video detectors are also used in some traffic signal actuation systems.To facilitate traffic signal light actuation, a video camera is placedhigh above a signal arm such that the video camera's view covers oneapproach to the intersection. The video signal from the camera isdigitally processed to create detections in the defined zones. Usingvideo detectors an intersection can be monitored on a per approach basis(that is all the lanes of an approach), as opposed to the per detectionzone basis used with inductive loops. Since a dedicated mounting arm isoften necessary the installation of a video detector system can also beexpensive and time consuming. Furthermore, video detectors require agreat deal of maintenance since the video cameras often fail and theyrequire cleaning. The performance of video detection is affected byvisibility conditions such as snow, rain, fog, direct light on thecamera at dusk and dawn, and the lighting of the roadway at night.

Microwave detectors have also been used in intersections to providedetection coverage over limited areas. At least one microwave detectorhas a limited degree of mechanical and electrical steering. Further, thecoverage is typically over a small portion of the intersection.

Other microwave sensors have included multiple receive antennas but haveincluded only a single transmit antenna that has a very broad main beamor even may be an omni-directional antenna. Systems that employ only onebroad beam or omni-directional transmit antenna typically cannot achievean appropriately reduced side lobe power level. Furthermore, thesesingle transmit antenna systems typically suffer from widening of themain lobe.

At least one microwave detector, which has been used for mid-blocktraffic detection applications near intersections, has two directionalreceive antennas and one directional transmit antenna. The multipleantennas create parallel radar beams that can be used to make velocitymeasurements as vehicles pass through the beams. However, the antennasof this device cannot cover enough of the intersection to providecoverage over a large area.

Acoustic sensors have also been used in intersections to cover limiteddetection zones. However, these sensors only monitor a limited area onan intersection approach and are subject to detection errors arisingfrom ambient noise.

BRIEF SUMMARY

The present invention extends to methods, systems, and computer programproducts for detecting roadway targets across beams. In someembodiments, computed target positions of targets detected using amultiple radar system are filtered. One or more targets are detected ina plurality of beams of the multiple beam radar system. Positions arecomputed for the one or more targets for a first detection period.Positions are computed for the one or more targets for a seconddetection period. The computed positions for the one or more targets arefiltered using a subset of computed positions from the first detectionperiod and using a subset of computed positions from the seconddetection period.

Targets can be detected in a plurality of beams of the multiple beamradar system using a variety of different mechanisms. For example,returns from the multiple beam radar system can be divided into a gridof range bins. Dividing returns into a grid of range bins includesdividing each beam in the plurality of beams into a plurality of rangebins of uniform varied distances from the multiple beam radar system.Each beam is divided into a plurality of range bins in accordance withthe uniform varied distances

In some embodiments, an energy peak is identified within a single beamof the multiple beam radar system. The identified energy peak canindicate a detected target.

In other embodiments, a multi-beam image is identified from within thereturns from the multiple beam radar system. The multi-beam image canspan a sub-plurality of the plurality of beams and span a plurality ofrange bins within the grid. An identified energy peak within themulti-beam image can indicate a detected target.

In further embodiments, a first comprehensive image is created fromreturns for each beam at a first detection period. A secondcomprehensive image is created from returns for each beam at a secondsubsequent detection period. The first comprehensive image is comparedto the second comprehensive image. Differences between the first andsecond images are identified. The identified differences can indicate adetected target.

In some embodiments, the computed target positions are filtered toremove errors from the computed positions. As part of this filteringprocess, track files are created for targets within a roadway. A targetlist for the roadway is accessed. A track file for each target in theroadway is maintained. Each track file includes target data for a targetthat is within the roadway. The target data includes target positiondata for a target, the target position data including at least one of: alast known position for the target and a predicted position for thetarget.

Maintaining track files includes accessing a currently computed positionfrom the target list and accessing a specified track file for anexisting target. If the specified track file has target position datacorresponding to the currently computed position, then it is determinedthat the currently computed position corresponds to a position of theexisting target. The determination can be made by comparing thecurrently computed position to the target position data in the accessedtrack file. The specified track file for the existing target is updatedwhen the currently computed position is determined to correspond to theposition of the existing target. On the other hand, a new track file iscreated for a new target when the currently computed position isdetermined not to correspond to the position of the existing target.

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

Additional features and advantages of the invention will be set forth inthe description which follows, and in part will be obvious from thedescription, or may be learned by the practice of the invention. Thefeatures and advantages of the invention may be realized and obtained bymeans of the instruments and combinations particularly pointed out inthe appended claims. These and other features of the present inventionwill become more fully apparent from the following description andappended claims, or may be learned by the practice of the invention asset forth hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the invention can be obtained, a moreparticular description of the invention briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered to be limiting of its scope, the invention will bedescribed and explained with additional specificity and detail throughthe use of the accompanying drawings in which:

FIG. 1 illustrates an embodiment of a traffic sensor.

FIG. 2A illustrates the traffic sensor of FIG. 1 in a roadwayintersection.

FIG. 2B illustrates the plurality of beams of the traffic sensor of FIG.1 being divided into a grid range bins.

FIG. 2C illustrates a detected target within the plurality of beams ofthe traffic sensor of FIG. 1.

FIG. 3 illustrates an example flow chart of a method for filteringcomputed target positions across a plurality of beams of a multiple beamradar system in a roadway.

FIG. 4A illustrates an example flow chart of a method for detectingtargets in a plurality of beams.

FIG. 4B illustrates an example flow chart of another method fordetecting targets in a plurality of beams.

FIG. 4C illustrates an example flow chart of another method fordetecting targets in a plurality of beams.

FIG. 5 illustrates an example flow chart of a method for performingfiltering of computed target positions by maintaining a track file.

FIG. 6 illustrates a portion of traffic sensor infrastructure forupdating track files for targets within a roadway intersection.

FIG. 7A illustrates an example of determining whether or not a computedtarget position corresponds to the position of an existing target in aroadway intersection.

FIG. 7B another example of determining whether or not a computed targetposition corresponds to the position of an existing target in a roadwayintersection.

FIG. 8 illustrates an example flow chart of another method for filteringtarget positions across a plurality of beams of a multiple beam radarsystem in a roadway.

DETAILED DESCRIPTION

The present invention extends to methods, systems, and computer programproducts for detecting roadway targets across beams. In someembodiments, computed target positions of targets detected using amultiple radar system are filtered. One or more targets are detected ina plurality of beams of the multiple beam radar system. Positions arecomputed for the one or more targets for a first detection period.Positions are computed for the one or more targets for a seconddetection period. The computed positions for the one or more targets arefiltered using a subset of computed positions from the first detectionperiod and using a subset of computed positions from the seconddetection period.

Targets can be detected in a plurality of beams of the multiple beamradar system using a variety of different mechanisms. For example,returns from the multiple beam radar system can be divided into a gridof range bins. Dividing returns into a grid of range bins includesdividing each beam in the plurality of beams into a plurality of rangebins of uniform varied distances from the multiple beam radar system.Each beam is divided into a plurality of range bins in accordance withthe uniform varied distances

In some embodiments, an energy peak is identified within a single beamof the multiple beam radar system. The identified energy peak canindicate a detected target.

In other embodiments, a multi-beam image is identified from within thereturns from the multiple beam radar system. The multi-beam image canspan a sub-plurality of the plurality of beams and span a plurality ofrange bins within the grid. An identified energy peak within themulti-beam image can indicate a detected target.

In further embodiments, a first comprehensive image is created fromreturns for each beam at a first detection period. A secondcomprehensive image is created from returns for each beam at a secondsubsequent detection period. The first comprehensive image is comparedto the second comprehensive image. Differences between the first andsecond images are identified. The identified differences can indicate adetected target.

In some embodiments, the computed target positions are filtered toremove errors from the computed positions. As part of this filteringprocess, track files are created for targets within a roadway. A targetlist for the roadway is accessed. A track file for each target in theroadway is maintained. Each track file includes target data for a targetthat is within the roadway. The target data includes target positiondata for a target, the target position data including at least one of: alast known position for the target and a predicted position for thetarget.

Maintaining track files includes accessing a currently computed positionfrom the target list and accessing a specified track file for anexisting target. If the specified track file has target position datacorresponding to the currently computed position, then it is determinedthat the currently computed position corresponds to a position of theexisting target. The determination can be made by comparing thecurrently computed position to the target position data in the accessedtrack file. The specified track file for the existing target is updatedwhen the currently computed position is determined to correspond to theposition of the existing target. On the other hand, a new track file iscreated for a new target when the currently computed position isdetermined not to correspond to the position of the existing target.

Embodiments of the present invention may comprise or utilize a specialpurpose or general-purpose computer including computer hardware, suchas, for example, a processor, as discussed in greater detail below.Embodiments within the scope of the present invention also includephysical and other computer-readable media for carrying or storingcomputer-executable instructions and/or data structures. Suchcomputer-readable media can be any available media that can be accessedby a general purpose or special purpose computer system.Computer-readable media that store computer-executable instructions arephysical storage media. Computer-readable media that carrycomputer-executable instructions are transmission media. Thus, by way ofexample, and not limitation, embodiments of the invention can compriseat least two distinctly different kinds of computer-readable media:computer storage media and transmission media.

Computer storage media includes RAM, ROM, EEPROM, CD-ROM or otheroptical disk storage, magnetic disk storage or other magnetic storagedevices, or any other medium which can be used to store desired programcode means in the form of computer-executable instructions or datastructures and which can be accessed by a general purpose or specialpurpose computer.

A “network” is defined as one or more data links that enable thetransport of electronic data between computer systems and/or modulesand/or other electronic devices. When information is transferred orprovided over a network or another communications connection (eitherhardwired wireless or a combination of hardwired or wireless) to acomputer, the computer properly views the connection as a transmissionmedium. Transmissions media can include a network and/or data linkswhich can be used to carry or desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer. Combinationsof the above should also be included within the scope ofcomputer-readable media.

Further, upon reaching various computer system components, program codemeans in the form of computer-executable instructions or data structurescan be transferred automatically from transmission media to computerstorage media (or vice versa). For example, computer-executableinstructions or data structures received over a network or data link canbe buffered in RAM within a network interface module (e.g., a “NIC”),and then eventually transferred to computer system RAM and/or to lessvolatile computer storage media at a computer system. Thus, it should beunderstood that computer storage media can be included in computersystem components that also (or even primarily) utilize transmissionmedia.

Computer-executable instructions comprise, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. The computer executable instructions may be, forexample, binaries, intermediate format instructions such as assemblylanguage, or even source code. Although the subject matter has beendescribed in language specific to structural features and/ormethodological acts, it is to be understood that the subject matterdefined in the appended claims is not necessarily limited to thedescribed features or acts described above. Rather, the describedfeatures and acts are disclosed as example forms of implementing theclaims.

Those skilled in the art will appreciate that the invention may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, mobile telephones,PDAs, pagers, routers, switches, traffic sensors, and the like. Theinvention may also be practiced in distributed system environments wherelocal and remote computer systems, which are linked (either by hardwireddata links, wireless data links, or by a combination of hardwired andwireless data links) through a network, both perform tasks. In adistributed system environment, program modules may be located in bothlocal and remote memory storage devices.

Accordingly, in this specification and in the following claims, acomputer system is also defined to include traffic sensors (e.g., sensor20 in FIG. 1).

In this specification and in the following claims, the term “roadwayintersection” is defined as the intersection of two or more roadways forautomobile and/or truck traffic including the approaches to theintersection and also includes an intersection of roadways with one ormore thoroughfares for other traffic, including the approaches to theintersection. Thoroughfares for other traffic may include pedestrianpaths and railways.

Embodiments of the invention include intersection traffic detectionproducts that: can be mounted above the roadway surface, monitor a wideportion of the roadway, and are robust to varying lighting and weatherconditions.

FIG. 1 is an example traffic sensor 20. Generally, traffic sensor 20 canbe used to detect objects (e.g., vehicles, pedestrians, etc.) at aroadway. As depicted, traffic sensor 20 includes antenna array 31,circuitry 11, signal generator 12, receive channel 13, processor 14, andmemory 38.

Generally, antenna array 31 is configured to create antenna beams overwhich a transmit signal is propagated and/or from which received signalsare received. In some embodiments, antenna array 31 creates multipleantenna beams that are steered so that the antennas overlap at their 3dB points creating continuous coverage over a 90 degree area.

Antenna array 31 can include a plurality (and potentially a largenumber) of transmit antennas and can include a plurality (andpotentially a large number) of receive antennas. Transmit antennas canbe configured to transmit signals into a roadway. Transmit antennas canbe directional antennas used to transmit a signal. Receive antennas canbe configured to receive reflections of signals reflected off of objectsin the roadway. The reflections can correspond to two dimensional imagedata for the roadway. Receive antennas can also be directional antennasused to receive (e.g., reflected) signals.

Using directional antennas (potentially for both transmit antennas andreceive antennas) has at least two advantages over the use of othertypes of antennas, including broad beam antennas. One advantage is thatthe sidelobe level in the two way antenna pattern is reduced. Anotheradvantage is that the width of the mainlobe in the two way antennapattern is also reduced.

Generally, the number of transmit and receive antennas used in anantenna area can be matched to the size of the area that is to becovered. For larger areas the number of transmit and receive antennascan be increased. In some embodiments, the number of transmit andreceive antennas is selected to provide sufficient angular resolution orsufficient coverage.

In some embodiments, instead of using a number of fixed beam antennas,an electronically steerable antenna is used to create beams that aresteered to different angles. For example, the electronically steerablebeam may be steered 10 degrees to the left for one detection period andit may be steered 20 degrees to the left in the next detection periodand so on.

Still in other embodiments, beam forming is used to create the antennabeams that are steered to different angles. In a sensor in which beamforming is used, data is collected from a number of antenna elements andis then combined using digital signal processing to create a beam thatis steered to the desired direction.

Signal generator 12 is configured to generate a radar signal. Generally,circuitry 11 is configured to provide a transmitting transmission pathbetween signal generator 12 and antenna array 31. Signals generated atsignal generator 12 can pass from signal generator 12, along thetransmitting transmission path, to antenna array 31 for transmission.The transmitting transmission path can include appropriate switches thatswitch the transmission path to each (e.g., transmitting) antenna in theantenna array 31 in sequence.

Circuitry 11 is also configured to provide a receiving transmission pathbetween antenna array 31 and receive channel 13. Reflected signalsreceived at antenna array 31 can pass from antenna array 31, along thereceive transmission path, to receive channel 13. The receivetransmission path can include a mixer that mixes down received reflectedsignals to baseband.

Receive channel 13 is configured to condition received reflections forcompatibility with processor 14. When appropriate, receive channel 13provides one or more of: multiplexing, filtering, and amplificationbefore providing received signals for analog to digital conversion. Insome embodiments, baseband signal lines are multiplexed to a singlesignal line.

Processor 14 processes signals corresponding to received reflections toconvert the signals into meaningful digital data (e.g., digital data36). In some embodiments, the processing algorithms combine the datafrom the plurality of antennas into one complete (e.g., two dimensional)image before detecting vehicles. Processor 14 can be a digital signalprocessor configured to convert received signals into digital data anddeliver digital data to external components, such as, for example,communication link 33 (e.g., to a display device or another computersystem), storage 37, and contact closure 39. Storage 37 can be acomputer-readable storage media, such as, for example, a magnetic disk,an optical disk, a flash drive, RAM, etc.)

Digital data 36 can include, for example, a sensor configuration,presence indications, vehicle detections, estimated vehicle speed, andtraffic statistics. Traffic statistics can include: vehicle counts perlane; vehicle counts per direction; vehicle counts per approach; turningcounts; average speeds per lane, direction, or approach; 85th percentilespeeds per lane, direction, or approach; occupancy per lane, direction,or approach; etc.

Processor 14 can also be configured to control signal generator 12. Forexample, processor 14 can send a signal activation command to signalgenerator 12 when signal generator 12 is to generate a signal.

As depicted, sensor 20 includes system memory 38 (e.g., RAM and/ROM).Processor 14 can utilize system memory 38 when processing digital data36. For example, sensor 30 can execute computer-executable instructionsstored in ROM to process digital data 36. During processing of digitaldata 36, processor 14 can store values in RAM and retrieve values fromRAM.

Also as depicted, sensor 20 includes storage 32. Storage 32 can includemore durable computer storage media, such as, for example, a flash driveor magnetic hard disk. Thus, sensor 20 can also executecomputer-executable instructions stored storage 32 and use RAM to storeand retrieve values during execution. In some embodiments,computer-executable instructions stored at sensor 20, when executed atprocessor 14, detect energy peaks in two dimensional image data for aroadway.

In this specification and in the following claims “track file” isdefined as a collection of data associated with a target (e.g.,vehicle), which is used to monitor the movements of that target, suchas, for example, in a roadway. A track file can contain information fora target, such as, for example, current position data that consists ofrange and azimuth angle information, starting position, positionhistory, current vector velocity, vector velocity history, predicatedposition, as well as radar return characteristics such as brightness,scintillation intensity, and signal spread in range. As such, based onsensor data, processor 14 can also create and store track files, suchas, for example, track files 34A, 34B, etc., in memory 38 or storage 32.Stored track files can be subsequently accessed and updated (e.g.,modified and deleted) as further information related to a target issensed. Accordingly, in other embodiments, computer-executableinstructions stored at sensor 20, when executed at processor 14, createand/or update track files for a roadway.

Signal generator 12 can be a radio frequency (“RF”) generator thatgenerates RF signals. For example, signal generator 12 can generate afrequency modulated continuous wave (“FMCW”) RF signal. The FMCW RFsignal can be generated via direct digital synthesis and frequencymultiplication. In these embodiments, circuitry 11 includes RF circuitryhaving RF switches. The RF switches are used to switch the transmissionpath for an RF signal to each (e.g., transmitting) antenna in theantenna array 31 in sequence.

In these embodiments, the RF circuitry is also configured to provide areceiving transmission path for received reflected RF signals. Receivechannel 13 can condition received reflected RF signals for compatibilitywith processor 14. When appropriate, receive channel 13 provides one ormore of: multiplexing, filtering, and amplification before providingreceived reflected RF signals for analog to digital conversion.

Also in these embodiments, the same antenna can be used to both transmitan RF signal and receive reflected RF signals. Accordingly, the numberof antennas in the antenna array can be reduced by half relative toembodiments in which separate transmit and receive antennas arerequired. Transmit antennas can be directional antennas used to transmitan RF signal. Similarly, receive antennas can be directional antennasused to receive reflected RF signals.

Embodiments of the invention include radar vehicular traffic sensorsthat use multiple radar beams to cover a (potentially wide) detectionarea and create position information within that detection area. Using amultiple radar beam system vehicle movements can be tracked as thevehicle position moves across the different beams.

FMCW RF radar systems can measure the range to the targets in the radarbeam. Each beam in a multiple beam system can overlap to some extentwith adjacent beams. In some embodiments, this results in there being nogaps in coverage. The system can measure the distance to targets in eachof the beams.

Accordingly, in some embodiments, the range to the targets in each ofthe antenna beams is determined through the use of an FMCW RF signal.The angle to targets in a roadway can be determined through the use ofthe individual antennas in the antenna array. As a result, the range andangle can be determined for targets in a large portion of a roadway.From this information a two dimensional image of the roadwayintersection can be constructed.

FIG. 2A depicts the traffic sensor 20 of FIG. 1 in a roadwayintersection 41. Sensor 20 utilizes multiple antenna beams 24A-24P.Circuitry 11 can be configured to switch radar signal transmissionbetween antenna beams 24A-24P on and off in sequence. Switchingcircuitry can control when each antenna beam is transmitting. A basebandmultiplexer can control when a received (e.g., reflected) signal isprocessed for an antenna.

Processor 14 can measure the range to targets in each of the antennabeams 24A-24P. The range is the distance between sensor 20 and anytargets, such as, for example, vehicle 26. Further, by using each of theantenna beams 24A-24P, sensor 20 can receive a radar return (e.g., areflection off of vehicle 26) from multiple azimuth angles and canmeasure the range to the targets at each of the azimuth angles. Themultiple azimuth angles can be measured in the horizontal plane. In thisway, processor 14 can create a two dimensional image showing thelocation of the targets (e.g., vehicle 26) in and/or approachingintersection 41. Processor 14 can create an image using a twodimensional orthogonal coordinate system, such as, for example, aCartesian coordinate system, a polar coordinate system, etc.

The plurality of beams in a multiple beam radar system can be divided ina grid of range bins. For example, FIG. 2B depicts the plurality ofbeams of sensor 20 within intersection 41. (However, the vehicles,intersection markings, and boundaries from FIG. 2A are removed forclarity). As depicted, beams 24A-24P are divided into a grid of rangebins 42. Range bins in grid 42 are of uniform varied distance rangesfrom sensor 20. Each beam is divided into a plurality of range bins inaccordance with the uniform varied distance ranges. The uniform varieddistance ranges are identified as range 1 through range 10.

Within the description and following claims, a particular range bin ingrid 42 can be identified by a combination of beam letter and rangenumber so as to differentiate the particular range bin from other rangesbins in grid 42. As such, adjacent range bins in the same range can bedifferentiated by beam letter. For example, beam 24C and range 9identify range bin C9 and beam 24D and range 9 identify bin D9. On theother hand, adjacent range bins in the same beam can be differentiatedby range number. For example, beam 24N and range 6 identify range bin N6and beam 24N and range 7 identify bin N7. Although not expresslydepicted in the Figures, other range bins may be referred to usingsimilar notations throughout this specification. For example, the rangebin corresponding to beam 24G and range 2 can be referred to as rangebin G2. Similarly, the range bin corresponding to beam 24L and range 6can be referred to as range bin L6. However, other range bin notationsare also possible.

Based on grid 42, sensor 20 can detect multi-beam images within returns(reflections) from targets in intersection 41. Multi-beam images canspan a plurality of the beams 24A-24P. Multi-beam images can also span aplurality of range bins within gird 42. The magnitude of the energyreflected from a particular range bin can correspond to the amount ofreflective area in the particular range bin. That is, when there is morereflective area in a range bin, the magnitude of energy detected in therange bin is likely to be greater. On the other hand, when there is lessreflective area in a range bin, the magnitude of energy detected in therange bin is likely to be lower.

Thus, it may be that a larger portion of a vehicle is with theboundaries of a specified range bin of grid 42. As such, other smallerportions of the vehicle may be within the boundaries of one or moreother range bins of 42. Thus, since a larger portion of the vehicle isin the specified range bin, the reflective area in the specified rangebin is likely greater than the reflective area in any of the one or moreother range bins. Accordingly, the magnitude of the identified energyfrom the specified range bin is also likely to be greater than themagnitude of the identified energy from the one or more other rangebins.

Sensor 20 can use a magnitude threshold to determine when identifiedenergy indicates a potential target. When the magnitude of identifiedenergy from a range bin is greater than (or equal to) the magnitudethreshold, sensor 20 can consider the identified energy as a potentialtarget. On the other hand, when the magnitude of identified energy froma range bin is less than the magnitude threshold, sensor 20 does notconsider the identified energy as a potential target.

When the magnitude of identified energy from a specified range binindicates a potential target, sensor 20 can then determine whether ornot the magnitude of identified energy from the specified range bin isan energy peak. That is, whether or not the magnitude of the specifiedrange bin is greater than the magnitude of the identified energy in anysurrounding adjacent range bins. In some embodiments, a target or atleast a larger portion (or largest portion of) a target is assumed to belocated in a range bin that is an energy peak.

Thus, when the magnitude of identified energy from the specified rangeis an energy peak, sensor 20 detects there to be a target present in thespecified range bin. For example, a larger portion of a vehicle may bepresent within the boundaries of the specified range bin. On the otherhand, when the magnitude of identified energy from the specified rangebin is not an energy peak, sensor 20 considers there not to be a targetpresent in the specified range bin. For example, a smaller portion of avehicle may be present within the boundaries of the specified range bin(and thus a larger portion of the vehicle is likely present in one ormore of the surrounding adjacent range bins).

When a target is detected (i.e., when the magnitude of identified energyin a specified range bin is greater than a threshold and greater thanany surrounding adjacent range bins), sensor 20 can use the magnitude ofthe identified energy in the specified range bin and the magnitude ofthe energy in any surrounding adjacent range bins to compute theposition of the target. In some embodiments, a two-dimensional Cartesiancoordinate system is used to more precisely represent positions on aroadway. For example, a Cartesian coordinate system can be used torepresent positions in intersection 41. As such, identified energymagnitudes from grid 42 can be used to calculate the position (e.g., Xand Y coordinates) of targets in intersection 41.

Turning to FIG. 2C, FIG. 2C depicts a detected target within theplurality of beams of the traffic sensor 20. FIG. 3 illustrates anexample flow chart of a method 300 for filtering computed targetpositions across a plurality of beams of a multiple beam radar system ina roadway. The method 300 will be described primarily with respect tothe data and components in FIGS. 2A-2C.

Method 300 includes an act of detecting one or more targets in aplurality of beams of a multiple beam radar system (act 301). Forexample, targets can be detecting in the plurality of beams of 24A-24Pof sensor 20. Targets can be detected using a variety of differentmechanisms. FIGS. 4A, 4B, and 4C illustrate example flow charts ofmethods for detecting targets in a plurality of beams of the multiplebeam radar system. Any of the methods depicted in FIG. 4A, 4B, or 4C canbe used to implement act 301. FIGS. 4A, 4B, and 4C will now be describedafter which the remaining acts of method 300 will be described.

More specifically, FIG. 4A illustrates an example flow chart of a method400 for detecting targets in a plurality of beams. Method 400 will bedescribed with respect to the elements depicted in FIGS. 2A-2C.

Method 400 includes an act of dividing returns from the multiple beamradar system into a grid of range bins, dividing returns into a grid ofrange bins including dividing each beam in the plurality of beams into aplurality of range bins of uniform varied distances from the multiplebeam radar system, each beam divided into a plurality of range bins inaccordance with the uniform varied distances (act 401). For example, asdepicted in FIG. 2B, the returns (reflections) corresponding to beams ofsensor 20 can be divided into grid 42.

Method 400 includes an act of identifying a multi-beam image within thereturns from the multiple beam radar system, the multi-beam imagerepresenting a target within the roadway, the multi-beam image spanninga sub-plurality of the plurality of beams, the multi-beam image alsospanning a plurality of range bins within the grid of range bins (act402). For example, turning now to FIG. 2C, sensor 20 can detect an imagethat spans range bins E5, D5, E6, D6, and C6 (as indicted by thehatching within these range bins).

Method 400 includes an act of identifying an energy peak within themulti-beam image (act 403). For example, sensor 20 can identify anenergy peak in range bin D6 (as indicated by cross-hatching in range binD6). Identifying an energy peak can include for a specified range bin inone of the beams of the sub-plurality of beams, an act of determiningthat the magnitude of the identified energy in the specified range binis above a specified threshold (act 404). Identifying an energy peak canalso include for the specified range bin, an act of determining that themagnitude of the identified energy in the specified range bin is greaterthan the magnitude of the identified energy in any of the surroundingadjacent range bins within the grid of range bin (act 405).

For example, sensor 20 can measure the magnitude of identified energy ineach range bin in grid 42 at specified intervals. For the identifiedenergy magnitudes, sensor 20 can determine if any of the identifiedmagnitudes are greater than (or equal to) a magnitude threshold. Forexample, as depicted in FIG. 2C, sensor 20 can determine that themagnitude of identified energy received from range bins D6 and E5 isgreater than magnitude threshold 271. For each of range bins D6 and E5,sensor 20 compares the identified energy magnitude to the identifiedenergy magnitude received from any surrounding adjacent range bins. Forexample, sensor 20 can compare the identified energy magnitude receivedform range bin D6 to the identified energy magnitudes received fromrange bins E5, D5, C5, E6, C6, E7, D7, and C7. Similarly, sensor 20 cancompare the identified energy magnitude received from range bin E5 tothe identified energy magnitudes receive from range bins F4, E4, C4, F5,C5, F6, E6, and D6.

From the comparison, sensor 20 can determine that the identified energymagnitude received from D6 is greater than identified energy magnitudereceived from any of its surrounding adjacent range bins. Sensor 20 canalso determine that the identified energy magnitude received from E5 isnot greater than identified energy magnitude received from any of itssurrounding adjacent range bins. That is, the identified energymagnitude received from range bin D6 is greater than the identifiedenergy magnitude received from range bin E5. As such, range bin D6 isidentified as an energy peak. However, range bin E5 is not identified asan energy peak. Since range bins D6 and E5 are adjacent range bins,sensor 20 determines that the identified energy magnitude received fromranges bins D6 and E5 is likely from the same target (e.g., vehicle 26).Further, since identified energy magnitude received from range bin D6 isgreater, sensor 20 determines that a larger portion of the target is inrange bin D6. Thus, it is also likely that a smaller portion of the sametarget (e.g., vehicle 26) is in range bin E5.

Method 400 can be repeated as appropriate to identify other targets inintersection 41, as well as identifying new positions of existingtargets in intersection 41. Thus, in some embodiments, an energy peak isidentified within a multi-beam image to detect a target.

In other embodiments, detecting targets in a plurality of beams includesidentifying an energy peak within a single beam of a multiple beam radarsystem to detect a target. For example, turning now to FIG. 4B, FIG. 4Billustrates an example flow chart of another method 420 for detectingtargets in a plurality of beams. Method 420 will be described withrespect to the elements depicted in FIGS. 2A-2C.

Method 420 includes an act of dividing returns from the multiple beamradar system into a grid of range bins, dividing returns into a grid ofrange bins including dividing each beam in the plurality of beams into aplurality of range bins of uniform varied distances from the multiplebeam radar system, each beam divided into a plurality of range bins inaccordance with the uniform varied distances (act 421). Act 421 can beperformed similarly or even identical to act 401 from method 400.

Method 420 includes an act of identifying an energy peak within a singlebeam of the multiple beam radar system (act 422). For example, turningnow to FIG. 2C, sensor 20 can detect an energy peak in beams 24C, 24D,and 24E.

Identifying an energy peak within a single beam can include for aspecified range bin in one of the beams of the sub-plurality of beams,an act of determining that the magnitude of the identified energy in thespecified range bin is above a specified threshold (act 423).Identifying an energy peak can also include for the specified range bin,an act of determining that the magnitude of the identified energy in thespecified range bin is greater than the magnitude of the identifiedenergy in both of the adjacent range bins (act 424). For example, inFIG. 2C range bin D6 is compared to range bin D5 and to range bin D7 andif the energy in D6 is greater than the energy in these bins then it isa peak.

Act 422 can be repeated for different beams within the multiple beamradar system and can be repeated at different points in time so thatwhile each individual target is only detected in a single beam, thetargets collectively are detected in a plurality of beams.

In further embodiments, detecting targets within a plurality of beamsincludes comparing differences between created comprehensive images. Forexample, turning now to FIG. 4C, FIG. 4C illustrates an example flowchart of another method 440 for detecting targets in a plurality ofbeams. Method 440 will be described with respect to the elementsdepicted in FIGS. 2A-2C.

Method 440 includes an act of dividing returns from the multiple beamradar system into a grid of range bins, dividing returns into a grid ofrange bins including dividing each beam in the plurality of beams into aplurality of range bins of uniform varied distances from the multiplebeam radar system, each beam divided into a plurality of range bins inaccordance with the uniform varied distances (act 441). Act 441 can beperformed similarly or even identical to act 401 from method 400 or toact 421 from method 420.

Method 440 includes an act of creating a first comprehensive image fromthe returns for each beam at a first detection period (act 442). In someembodiments, creating a comprehensive image includes organizing dividedreturns for each of the beams of the multiple beam radar system into ablock of memory. For example, sensor 20 can create a first comprehensiveimage by organizing divided returns for each of beams 24A-24P into ablock of memory. The first comprehensive image can be created at a firstdetection period for sensor 20.

Method 440 includes an act of creating a second comprehensive image fromthe returns for each beam at a second detection period, the seconddetection period occurring subsequent to the first detected period (act443). For example, sensor 20 can also create a second comprehensiveimage by organizing divided returns for each of beams 24A-24P into ablock of memory. The second comprehensive image can be created at asecond detection period for sensor 20. The second detection period forsensor 20 can occur after the first detection period for sensor 20.

Method 440 includes an act of comparing the first comprehensive imagefrom the first detection period to the second comprehensive image fromthe second detection period (act 444). In some embodiments, thecomparison includes subtracting the radar return for each range bin ineach beam in the first comprehensive image from the radar return foreach range bin in each beam in the second comprehensive image. Forexample, the radar return in each bin in grid 42 at a first time can besubtracted from the radar return in each bin of grid 42 at a secondsubsequent time to compare comprehensive images created by sensor 20.

Method 440 includes an act of identifying differences between the firstand second comprehensive images (act 445). For example, sensor 20 canidentify differences in returns in the bins of grid 42 over time. Thesedifferences can represent target detections. Act 445 can be repeated anumber of times until targets in a comprehensive image are identified.

Thus as described, a variety of different mechanisms can be used todetect targets in a plurality of beams (e.g., in grid 42). Upondetecting targets in a plurality of beams, a variety of differentcomputations can be performed based on the detected targets.

Referring now back to FIG. 3, Method 300 includes an act of computingpositions for the one or more targets for a first detection period (act302). For example, sensor 20 can detect the position of one or moretargets (e.g., vehicle 26) in intersection 41 for a first detectionperiod. Method 300 includes an act of computing positions for the one ormore targets for a second detection period (act 303). For example,sensor 20 can detect the position of one or more targets (e.g., vehicle26) in intersection 41 for a second (subsequent) detection period.

In some embodiments, target positions are computed based on themagnitude of the identified energy in the specified range bin and themagnitude of the identified energy in any of the surrounding adjacentrange bins. For example, sensor 20 can compute target position 202 (ofvehicle 26) from the identified energy magnitudes received from rangebins E5, D5, C5, E6, D6, C6, E7, D7, and C7. Computed target position202 can include coordinates 203 (e.g., x and y coordinates) indicating atwo-dimensional position of vehicle 26 in intersection 41.

In some embodiments, centroid x and y coordinates are calculated inaccordance with the following equation:

$\left( {x_{centroid},y_{centroid}} \right) = \frac{\sum\limits_{n = 1}^{N}{\left( {x_{n},y_{n}} \right) \cdot M_{n}}}{\sum\limits_{n = 1}^{N}M_{n}}$where N=the number of range bins used in the centroid calculation. Forrange bins that are not on the edge of grid 42, N=9, the range bin ofinterest (a range bin having an energy peak) and the eight surroundingbins. (x_(n),y_(n)) represents the x and y coordinates of the center ofthe range bin. For side or corner range bins the value of N can differ.M_(n) represents the identified energy magnitude received from the rangebin.

A plurality of different positions for a target can potentially becomputed. For example, for a target with spatial extent along a lane,the position of the foremost point along a lane and the position of theback most point along a lane could be computed.

Method 300 includes an act of filtering the computed positions for theone or more using a subset of computed positions from the firstdetection period and using a subset of computed positions from thesecond detection period (act 304). In some embodiments, filtering thecomputed positions includes both spatial and temporal filtering in whichthe computed target position is filtered in both position and in time.For example, sensor 20 can spatially and temporally filter computedtarget positions detected within grid 42.

Computed target positions will have errors that can be at leastpartially removed by filtering. For example, vehicles travel along pathsdictated by the principles of velocity and acceleration. The computedpositions, however, may have errors that could represent movements thatwould be impossible for a vehicle. These errors can be filtered outusing a number of different methods.

One mechanism for spatially and temporally filtering is facilitatedthrough the use of a track file. When maintaining a track file using acomputed position from one detection period, the target may be detectedin one beam of the multiple beam radar system as previously described.When the track file is maintained in another detection period, however,the target may be detected in a different beam of the multiple beamradar system. Thus, the track file has been maintained using thecomputed positions of targets in a plurality of beams even though in asingle detection period the track file was maintained using computedpositions of a target in a single beam.

In some embodiments, a target list is used to update track files for aroadway. When multiple targets are detected and multiple positions arecomputed in a single detection period, then the computed targetpositions are added to a target list.

Turning now to FIG. 6, FIG. 6 illustrates a portion of traffic sensor 20for updating track files 34 for targets within roadway intersection 41.As depicted, sensor 20 includes track file maintenance module 401. Trackfile maintenance module 401 is configured to access a target list andtrack files. From the target list and track files, track filemaintenance module 401 determines if a computed target position in thetarget list corresponds to the position of a new target or to a newposition of an existing target. For example, track file maintenancemodule 401 can access target list 201 and track files 34 and determineif computed target position 202 is the position of a new target inintersection 41 or computed target position 202 is a new position of anexisting target in intersection 41.

Turning back to FIG. 5, FIG. 5 illustrates an example flow chart 500 ofa method for performing filtering by maintaining a track file. Themethod 500 will be described primarily with respect to the data andcomponents in FIG. 6.

Method 500 includes an act of accessing a currently computed positionfrom the target list (act 501). For example, track file maintenancemodule 401 can access computed position 202, including coordinates 203,from target list 201. Computed position 202 can indicate the position ofa target in intersection 41

Method 500 includes an act of accessing a specified track file for anexisting target, the specified track file having target position datathat may correspond to the currently computed position (act 502). Forexample, track file maintenance module 401 can access one of track files34. Each track file can include target data for a target that is withinintersection 41. Target data can include target positioning dataincluding at least one of: a last known position for the target and apredicted position for the target. For example, track file 34B caninclude target data 35B, including last known position 601 and predictedfuture position 604 for a target in intersection 41. Depending on anamount of time sensor 20 has been tracking a target, a predictedposition may not be available, or may be more or less precise. Forexample, it may be difficult to predict a position for a target whensensor 20 has not tracked the target long enough to formulate areasonable estimate of speed and/or direction for the target. Thus, asmore information for a target is obtained, predictions of futurepositions can also become more precise.

For example, track file maintenance module 401 can access track file 34Bfor a target in intersection 41. Track file 34B can be selected due tohaving location data with a last known position and/or predictedlocation that is closer to computed position 202 than location data inother track files. Alternately, track file maintenance module 401 canaccess each track file 34 individually for comparison to computedposition 202.

Method 500 includes an act of determining if the currently computedposition is a position of the existing target by comparing the currentlycomputed position to the position data in the accessed track file (act503). For example, track file maintenance module 401 can determine ifcomputed position 202 is a position of an existing target in roadwayintersection 41 by comparing coordinates 203 to location data 35B.

In some embodiments, a computed position in a target list is compared toa last known position from a target. If the computed position in thetarget list is within a specified distance of a last known position,track file maintenance module 401 determines that the computed positionfrom the target list is a new position for an existing target. Forexample, referring to FIG. 7A, FIG. 7A illustrates an example ofdetermining whether or not a computed target position is the position ofan existing target in a roadway.

As depicted in FIG. 7A, last known position 601 and computed position202 are depicted some distance apart. Track file maintenance module 401can calculate calculated distance 776 between last known position 601and computed position 202 from coordinates 602 and coordinates 203(e.g., both 602 and 203 being two-dimensional Cartesian coordinates).Track file maintenance module 401 can compare calculated distance 776 toa specified radius 713 to determine whether or not computed position 202is a new position for the target previously detected at last knownposition 601. The specified radius 713 defines a circle (e.g., specifiedcircle 723) that is centered at the last known position 601 and has thespecified radius 713.

Thus, if the specified distance radius is specified radius 713, trackfile maintenance module 401 determines that computed position 202 is anew position for a target previously detected at last known position 601in intersection 41 (i.e., calculated distance 776 is less than specifiedradius 713 and computed position 202 is within specified circle 723). Onthe other hand, if the specified distance is specified radius 712, trackfile maintenance module 401 determines that computed position 202 is theposition of a new target in intersection 41 (i.e., calculated distance776 is greater than specified radius 712 and computed position 202 isoutside of specified circle 722).

In some embodiments, a computed position in a target list is compared toa predicted location for a target. If the computed position in thetarget list is within a specified distance radius of the predictedlocation, track file maintenance module 401 determines that the computedposition from the target list corresponds to a new position for anexisting target. For example, referring to FIG. 7B, FIG. 7B illustratesan example of determining whether or not a computed target position isthe position of an existing target in a roadway intersection.

As depicted in FIG. 7B, predicted position 604 and computed position 202are depicted some distance apart. Predicted position 604 is derived fromlast known position 601 and predicted travel path 707 (e.g., the speedand direction of a target in intersection 41). Track file maintenancemodule 401 can calculate calculated distance 777 between predictedposition 604 and computed position 202 from coordinates 606 andcoordinates 203 (e.g., both 606 and 203 being two-dimensional Cartesiancoordinates). Track file maintenance module 401 can compare calculateddistance 777 to a specified distance radius to determine whether or notcomputed position 202 corresponds to a new position for the targetpreviously detected at last known position 601.

Thus, if the specified distance radius is specified distance radius 716,track file maintenance module 401 determines that computed position 202corresponds to a new position for the target previously detected at lastknown position 601 in intersection 41 (i.e., calculated distance 777 isless than specified radius 716 and computed position 202 is withinspecified circle 726). On the other hand, if the specified distanceradius is specified radius 714, track file maintenance module 401determines that computed position 202 corresponds to the position of anew target in intersection 41 (i.e., calculated distance 777 is greaterthan specified radius 714 and computed position 202 is outside ofspecified circle 724).

Turning back to FIG. 5, method 500 includes an act of updating thespecified track file for the existing target when the currently computedposition is determined to correspond to the position of the existingtarget (act 504). For example, track file maintenance module 401 canupdate location data 35B of track file 34B by filtering computedposition 202 using either last known position 601 or predicted position604 to result in a new last known position to be used in the nextdetection period. Method 500 also includes an act of creating a newtrack file for a new target when the currently computed position isdetermined not to correspond to the position of the existing target (act505). For example, track file maintenance module 401 can create trackfile 34C (including computed position 202) for a new target inintersection 41.

Using track files to filter computed positions, which aids in thereduction of errors, can be done in many different ways. In someembodiments, a leaky integrator, also referred to as a single poleinfinite impulse response (IIR) filter, is used to filter the computedpositions. For example, when a position is computed that corresponds toa target with an existing track file, this computed position is combinedwith the last known position stored in the track file by weighting eachof the values by the predetermined filter coefficients and then summingthe two values. The result is used as the last known position for thenext detection period as shown in the following equation:P ₁ ^(Last Known) =a ₁ ·P _(t-1) ^(Last Known) +b ₀ ·P ₁ ^(Computed)whereinP₁ ^(Last Known)is the value stored as the last known position for use in the nextdetection period,P_(i-1) ^(Last Known)is the last known position that was stored during the previous detectionperiod, andP₁ ^(Computed)is the newly computed target position. a₁ and b₀ are the predeterminedfilter coefficients.

In some embodiments, the computed position is filtered using thepredicted position instead of the last known position. In theseembodiments, the last known position is used to calculate the predictedposition before the filtering is performed as shown in the followingequations:P ^(Predicted) _(i) =ν×Δt+P ^(Last Known) _(i-1)P ₁ ^(Last Known) =a ₁ ·P ₁ ^(Predicted) +b ₀ ·P ₁ ^(Computed)whereinP₁ ^(Predicted)

is the predicted position that is calculated from the velocity of thetarget, v, and the time between detection periods, Δt. The velocity ofthe target can be estimated by calculating the change in position overtime. Errors in this calculation can be reduced by averaging severalmeasurements. For example, one method of calculating the velocityconsists of averaging a predetermined number of calculated positions tocreate a first average position and then averaging a predeterminednumber of subsequent calculated positions to create a second averageposition. The velocity of the target can then be calculated by dividingthe difference between the first and second average positions by thetime required to create an average position.

FIG. 8 illustrates an example flow chart of a method 800 for filteringtarget positions across a plurality of beams of a multiple beam radarsystem in a roadway.

Method 800 includes an act of dividing returns from a multiple beamradar system from a first detection period into a grid of range bins,dividing returns into a grid of ranges bins including dividing each beamin the plurality of beams in to a plurality of range bins of uniformvaried distance ranges from the multiple beam radar system, each beamdivided into a plurality of range bins in accordance with the uniformvaried distance ranges (act 801). Act 801 can be performed similarly oreven identical to act 401 from method 400, to act 421 from method 420,or act 441 from method 440 for a first detection period.

Method 800 includes an act of creating a comprehensive image from thereturns for each beam from the first detection period (act 802). Act 802can be performed similarly or even identical to acts 442 of method 440.For example, in some embodiments, creating a comprehensive imageincludes organizing the divided returns for each of the beams of themultiple beam radar system into a block of memory.

Method 800 includes an act of dividing returns from the multiple beamradar system for a second detection period into the grid of range bins(act 803). Act 803 can be performed similarly or even identical to act401 from method 400, to act 421 from method 420, or act 441 from method440 for a second detection period.

Method 800 includes an act of creating a comprehensive image from thereturns for each beam from the second detection period (act 804). Act804 can be performed similarly or even identical to acts 443 of method440.

Method 800 includes an act of filtering the comprehensive image from thesecond detection period using a comprehensive image from the firstdetection period (act 805). In some embodiments, filtering is performedby filtering the radar return in each range bin and beam with the radarreturn in the corresponding range bin and beam from anothercomprehensive image. Method 800 includes an act of detecting targetsusing the filtered comprehensive image (act 806). Targets can bedetected similarly or even identical to the detection mechanismsdescribed in methods 400, 420, and 440.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

What is claimed:
 1. A traffic sensor for monitoring a roadway, thetraffic sensor comprising: a radar system including a plurality of beamsand configured to transmit signals into a roadway and to receivereflections of signals reflected off of objects in the roadway using theplurality of beams; and a computer system coupled with the radar systemand configured to: detect one or more targets in the plurality of beamsof the radar system; compute a first position for one or more detectedtargets for a first detection period; compute a second position for oneor more detected targets for a second detection period; derive at leastone filtered computed position for at least one of the one or moredetected targets using the first computed position from the firstdetection period and the second computed position from the seconddetection period.
 2. The traffic sensor of claim 1, wherein deriving afiltered computed position for the one or more detected targets furthercomprises using an additional subset of computed positions from thefirst detection period.
 3. The traffic sensor of claim 1, whereinderiving a filtered computed position for the one or more detectedtargets further comprises using an additional subset of computedpositions from the second detection period.
 4. The traffic sensor ofclaim 1, wherein deriving a filtered computed position for the one ormore targets further comprises using a subset of both the first computedposition from the first detection period and the second computedpositions from the second detection period.
 5. The traffic sensor ofclaim 1, wherein the radar system comprises: transmit antennas includinga plurality of beams and configured to transmit signals into the roadwayusing the plurality of beams, the signals being frequency modulatedcontinuous wave radio frequency signals; and receive antennas configuredto receive the reflections of signals off of objects in the roadwayusing the plurality of beams.
 6. The traffic sensor of claim 1, whereinthe computer system comprises: system memory; one or more processorselectronically coupled to the system memory; at least onecomputer-readable storage device electronically coupled to the one ormore processors, the at least one computer-readable storage devicehaving stored thereon instructions that when executed by the one or moreprocessors cause the computer system to detect the one or more targets,compute the first positions for the first detection period, compute thesecond positions for the second detection period, and derive thefiltered computed positions.
 7. The traffic sensor of claim 1, whereindetecting one or more targets in the plurality of beams of the radarsystem comprises identifying at least one energy peak within amulti-beam image generated using the radar system's plurality of beams.8. The traffic sensor of claim 1, wherein the first and second computedpositions are stored in a target list.
 9. The traffic sensor of claim 8,wherein if the computed positions stored in the target list are within aspecified distance of a last known position for at least one of the oneor more detected targets, the computer system determines that thecomputed positions from the target list represent new positions for anexisting target.
 10. A traffic control system comprising: a trafficsensor for monitoring a roadway, the traffic sensor comprising: a radarsystem including a plurality of beams and configured to transmit asignal into the roadway and to receive reflections of the signal off ofobjects in the roadway using the plurality of beams; and a computersystem coupled to the radar system and configured to: detect one or moretargets in the plurality of beams of the radar system; compute firstpositions for the one or more targets for a first detection period;compute second positions for the one or more targets for a seconddetection period; and filter the computed position of at least one ofthe one or more detected targets using one or more first computedpositions from the first detection period and one or more secondcomputed positions from the second detection period.
 11. The trafficcontrol system recited in claim 10, wherein the computer system isfurther configured to filter the computed position through both spatialand temporal filtering.
 12. The traffic control system recited in claim10, wherein the traffic control system further comprises a trafficcontrol device configured to actuate a traffic signal based on the atleast one filtered computed position for the one or more targets. 13.The traffic control system recited in claim 10, wherein the computersystem is further configured to send a signal to a traffic controldevice configured to actuate a traffic signal based on the filteredposition for the one or more targets.
 14. The traffic control systemrecited in claim 10, further comprising a second traffic sensor formonitoring a second roadway.
 15. The traffic control system recited inclaim 14, further comprising: a second traffic control device configuredto actuate a second traffic signal based on input from the secondtraffic sensor; and a data network that links the sensor and trafficcontrol device with the second sensor and second traffic control device.16. A method for deriving filtered positions for targets detected in aroadway across a plurality of beams of a radar system, the methodcomprising: detecting one or more targets in the plurality of beams ofthe radar system; computing a first position for one or more detectedtargets for a first detection period; computing a second position forone or more detected targets for a second detection period; deriving atleast one filtered computed position for at least one of the one or moredetected targets using the first computed position from the firstdetection period and the second computed position from the seconddetection period.
 17. The method of claim 16, wherein target positionsfor the one or more detected targets are computed based on a magnitudeof identified energy in a specified area of the roadway that is coveredby the plurality of beams of the radar system.
 18. The method of claim17, wherein the target positions for the one or more detected targetsare further based on a specified range bin and a magnitude of identifiedenergy in one or more surrounding adjacent range bins.
 19. The method ofclaim 17, wherein at least one of the computed target positions includescoordinates indicating a two-dimensional position of a vehicle in theroadway.
 20. The method of claim 19, wherein centroid coordinates arecalculated using the following equation:${\left( {x_{centroid},y_{centroid}} \right) = \frac{\sum\limits_{n = 1}^{N}{\left( {x_{n},y_{n}} \right) \cdot M_{n}}}{\sum\limits_{n = 1}^{N}M_{n}}},$where N equals a number of range bins implemented by the radar system.